code: def test_parameter_check_anova_warning(params, X, n_non_zeros):
      dft = DiscreteFourierTransform(**params, anova=True)
      msg = (
          "The number of non constant Fourier coefficients \\({0}\\) "
          "is lower than the number of coefficients to keep \\({1}\\). "
          "The number of coefficients to keep is truncated to {2}."
      ).format(n_non_zeros, params["n_coefs"], n_non_zeros)
      with pytest.warns(UserWarning, match=msg):
          dft.fit(X, np.random.randint(2, size=X.shape[0]))
  
file_path: pyts/pyts/approximation/tests/test_dft.py
imports: import numpy
  import pytest
  import re
  from sklearn.feature_selection import f_classif
  from pyts.approximation import DiscreteFourierTransform
label_desc: Use image node_id 3 for calling a global function with example usage: test_parameter_check_anova_warning(params, X, n_non_zeros) without return types